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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Plant Sci.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Plant Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Plant Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1664-462X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fpls.2026.1733839</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Real-time chlorophyll fluorescence monitoring reveals dynamic acclimation of lettuce to temperature and light stress in controlled environments</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Nam</surname><given-names>Suyun</given-names></name>
<uri xlink:href="https://loop.frontiersin.org/people/3135753/overview"/>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Ferrarezi</surname><given-names>Rhuanito Soranz</given-names></name>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/421293/overview"/>
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<aff id="aff1"><institution>Department of Horticulture, University of Georgia</institution>, <city>Athens</city>, <state>GA</state>,&#xa0;<country country="us">United States</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Rhuanito Soranz Ferrarezi, <email xlink:href="mailto:ferrarezi@uga.edu">ferrarezi@uga.edu</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-02-10">
<day>10</day>
<month>02</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>17</volume>
<elocation-id>1733839</elocation-id>
<history>
<date date-type="received">
<day>28</day>
<month>10</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>15</day>
<month>01</month>
<year>2026</year>
</date>
<date date-type="rev-recd">
<day>07</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Nam and Ferrarezi.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Nam and Ferrarezi</copyright-holder>
<license>
<ali:license_ref start_date="2026-02-10">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<p>Real-time monitoring of photosynthetic efficiency can improve our understanding of plant stress responses. In this study, we used a high-frequency chlorophyll fluorescence (CF) monitoring system to investigate the effects of combined temperature and light effects on lettuce. Plants were exposed to three temperatures (18, 25, and 32&#xa0;&#xb0;C) and two light intensities (150 and 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>) for one week, and CF parameters were measured every 30 minutes. Gas exchange measurements were conducted at 2 and 7 days after treatment (DAT). High light combined with low temperature initially suppressed &#x3a6;<sub>PSII</sub> but gradually improved via reductions in quantum yield of non-regulated energy dissipation (&#x3a6;<sub>NO</sub>), indicating adjustments in the photosynthetic machinery. While the quantum yield of non-photochemical quenching (&#x3a6;<sub>NPQ</sub>) decreased sharply only on the first day, &#x3a6;<sub>NO</sub> continued to decline, highlighting its role in longer-term acclimation. In contrast, high temperatures enhanced CO<sub>2</sub> assimilation through elevated stomatal conductance; however, the maximum efficiency of PSII (<italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub>) remained suppressed (~0.81), suggesting sustained photoinhibition. The relationship between electron transport rate (ETR) and photosynthetic rate (<italic>A</italic>) varied with temperature and time, indicating that the efficiency of converting photochemical energy into carbon assimilation depended on stress conditions and the acclimation stage. However, cumulative ETR integrated over the experiment period was significantly associated with shoot dry weight independent of temperature conditions, indicating that temporally integrated CF metrics retain predictive value for growth, unlike instantaneous CF parameters. These findings demonstrate that high-resolution CF monitoring captures subtle and dynamic photosynthetic responses that are not detectable via single-point gas exchange measurements alone. The ability to interpret changes in CF parameters in real-time provides valuable insights into plant acclimation and stress physiology for the optimization of environmental conditions in controlled environment agriculture systems.</p>
</abstract>
<kwd-group>
<kwd>abiotic stress</kwd>
<kwd>chlorophyll fluorescence</kwd>
<kwd>controlled environment agriculture</kwd>
<kwd>light acclimation</kwd>
<kwd>photosynthetic efficiency</kwd>
<kwd>temperature stress</kwd>
</kwd-group>
<funding-group>
<award-group id="gs1">
<funding-source id="sp1">
<institution-wrap>
<institution>National Institute of Food and Agriculture</institution>
<institution-id institution-id-type="doi" vocab="open-funder-registry" vocab-identifier="10.13039/open_funder_registry">10.13039/100005825</institution-id>
</institution-wrap>
</funding-source>
</award-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This research was funded by the USDA-NIFA-SCRI, award number 2018-51181-28365, project &#x201c;LAMP: Lighting approaches to maximize profits&#x201d;, USDA AFRI FAS Program A1521 5a, award number 2026-67021-45822, project &#x201c;Chlorophyll fluorescence-based biofeedback system to control LED lighting in greenhouses and vertical farms&#x201d;, the Department of Horticulture, the College of Agricultural and Environmental Sciences, and the Office of the Senior Vice President for Academic Affairs and Provost.</funding-statement>
</funding-group>
<counts>
<fig-count count="9"/>
<table-count count="4"/>
<equation-count count="5"/>
<ref-count count="52"/>
<page-count count="10"/>
<word-count count="10788"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Crop and Product Physiology</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Maintaining optimal photosynthetic performance in controlled environment agriculture (CEA) facilities is challenging under overcast or substandard environmental conditions. Limited or excessive light and temperature can induce physiological stress and increase reliance on energy-intensive environmental control, including supplemental lighting, shading systems, and heating, ventilation, and air conditioning (HVAC) systems. Therefore, optimizing photosynthetic efficiency is critical for maximizing crop productivity and improving energy use efficiency in CEA. High light intensity and temperature stress are among the most common environmental constraints in CEA production systems (<xref ref-type="bibr" rid="B50">Zhou et&#xa0;al., 2022</xref>). In general, photosynthetic efficiency decreases under excessive light, because surplus absorbed light energy is dissipated as heat and chlorophyll fluorescence to prevent photodamage to photosystem II (PSII) (<xref ref-type="bibr" rid="B44">Wimalasekera, 2019</xref>). Both heat and cold stress reduce photosynthetic efficiency and impair plant growth, primarily through the generation of reactive oxygen species (ROS) and photodamage to PSII components (<xref ref-type="bibr" rid="B16">Hussain, 2019</xref>).</p>
<p>However, the effect of high light and temperature stress varies depending on the combination of stressors and the duration of exposure. In particular, low temperatures combined with high light intensities can synergistically induce severe photoinhibition due to the overexcitation of PSII reaction centers (<xref ref-type="bibr" rid="B17">Janda et&#xa0;al., 2021</xref>). Prolonged exposure to both high light and high temperatures may lead to the irreversible inactivation of PSII due to the downregulation of PSII protein gene expression and associated repair mechanisms (<xref ref-type="bibr" rid="B21">Lu et&#xa0;al., 2017</xref>). Although this combination of stressors can mitigate oxidative damage through the accumulation of carbohydrates and carotenoids as protective and adaptive strategies, its effectiveness depends on the severity of the stresses and the crop species (<xref ref-type="bibr" rid="B51">Zhou et&#xa0;al., 2020</xref>).</p>
<p>Moreover, the stress responses are crop-specific and evolve over time, influenced by &#x201c;stress memory&#x201d;, defined as a history of exposure to different types of environmental stresses (<xref ref-type="bibr" rid="B6">Bruce et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B45">Yamori et&#xa0;al., 2014</xref>). For instance, the photosynthetic efficiency of lettuce (<italic>Lactuca sativa</italic>) increased significantly within a single day under high light, whereas cucumber (<italic>Cucumis sativus</italic>) maintained a constant level, indicating a species-specific response (<xref ref-type="bibr" rid="B30">Nam et&#xa0;al., 2025</xref>). Over longer periods, plants exhibit dynamic acclimation to light and temperature stresses through diverse physiological mechanisms such as chloroplast relocation, accumulation of accessory pigments, membrane fluidity adjustments, and leaf morphological changes (<xref ref-type="bibr" rid="B44">Wimalasekera, 2019</xref>). Monitoring real-time plant stress responses is essential for understanding how environmental factors dynamically influence photosynthetic performance. While single-leaf gas exchange remains a conventional method for assessing photosynthetic capacity and stomatal behavior, it is time-consuming and not suitable for high-frequency or long-term real-time monitoring. Consequently, temporal dynamics and acclimation patterns are often overlooked (<xref ref-type="bibr" rid="B13">Haworth et&#xa0;al., 2023</xref>). Whole-plant gas exchange systems enable the continuous measurement of whole-canopy photosynthesis, but their complexity reduces their practical applicability (<xref ref-type="bibr" rid="B34">Sakoda et&#xa0;al., 2025</xref>; <xref ref-type="bibr" rid="B41">van Iersel and Bugbee, 2000</xref>). Other traditional physiological assessments, such as biochemical or pigment analyses, are labor-intensive and destructive. Even though these more sophisticated systems have limited use, high-temporal-resolution monitoring is therefore critical for early stress detection, capturing within-day and long-term variability, and improving our understanding of plant-environment interactions (<xref ref-type="bibr" rid="B13">Haworth et&#xa0;al., 2023</xref>).</p>
<p>Chlorophyll fluorescence (CF) monitoring, based on the pulse amplitude modulation (PAM) technique, is a rapid, non-destructive, and highly sensitive method for detecting environmental stress. Parameters such as the maximum efficiency of PSII (<italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub>) serve as diagnostic indicators of photoinhibition under extreme temperature or excess light (<xref ref-type="bibr" rid="B22">Lysenko et&#xa0;al., 2022</xref>). Because CF measurements are non-destructive, repeated sampling enables detection of diurnal changes and acclimation responses. Linear electron transport rate (ETR) is generally well correlated with carbon dioxide (CO<sub>2</sub>) assimilation, offering a potential proxy for crop productivity. Additionally, CF allows detailed analysis of dynamic photochemical quenching, including regulated and unregulated energy dissipation (<xref ref-type="bibr" rid="B22">Lysenko et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B25">Maxwell and Johnson, 2000</xref>).</p>
<p>CF has been applied for early abiotic stress detection, crop phenotyping, prediction of flowering time, and development of productivity models (<xref ref-type="bibr" rid="B16">Hussain, 2019</xref>; <xref ref-type="bibr" rid="B18">Kalaji et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B47">Yu and Chen, 2023</xref>). It has also been implemented in real-time environmental control systems for artificial lighting. For example, a CF-based biofeedback system can collect CF parameters every 15 minutes via serial communication with a datalogger to dynamically adjust the lighting-emitting diode (LED) light intensity (<xref ref-type="bibr" rid="B30">Nam et&#xa0;al., 2025</xref>; <xref ref-type="bibr" rid="B42">van Iersel et&#xa0;al., 2016</xref>).</p>
<p>However, under photorespiratory stress conditions such as heat or drought, the relationship between ETR and carbon assimilation may weaken due to low CO<sub>2</sub> availability (<xref ref-type="bibr" rid="B22">Lysenko et&#xa0;al., 2022</xref>). This can cause a decoupling between fluorescence parameters and the actual carbon assimilation, which may limit the reliability of CF as a proxy for photosynthetic performance under certain stressful conditions. This response should be better studied to understand the factors needed to control lighting successfully.</p>
<p>The overall objective of this study was to demonstrate the utility of a high-frequency CF monitoring system for assessing plant physiological responses under temperature and light stress over time. It was hypothesized that high-frequency CF measurements can resolve temperature- and light-dependent stress responses and their interaction and acclimation dynamics over time, and that CF-derived metrics are associated with downstream physiological outcomes, including carbon assimilation and crop growth under stress conditions. This knowledge can be used for further automated lighting control using CF as a biofeedback control system.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Location</title>
<p>The study was conducted at the University of Georgia (College of Agricultural and Environmental Sciences, Department of Horticulture, Controlled Environment Agriculture Crop Physiology and Production Laboratory) in Athens, Georgia, USA (33 93&#x2019;11.36&#x201d; N, 83 36&#x2019;39.28&#x201d; W).</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Plant material, growth conditions</title>
<p>Lettuce &#x2018;Green Towers&#x2019; seeds (Johnny&#x2019;s Selected Seeds, Waterville, ME, USA) were sown into 10-cm square containers filled with a peat-perlite soilless substrate (Fafard 1P; SunGro Horticulture, Agawam, MA, USA). Seedlings were grown in a walk-in growth chamber illuminated with white LED light bars (RAY series with Physiospec indoor spectrum; Fluence Bioengineering, Austin, TX, USA) emitting 39% red, 40% green, 18% blue, and 3% far-red. Canopy-level photosynthetic photon flux density (PPFD) was maintained at 250 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, with a 16-h photoperiod (daily light integral [DLI] of 14.4 mol&#xb7;m<sup>-2</sup>&#xb7;d<sup>-1</sup>). Irrigation was supplied daily by an automated ebb-and-flow subirrigation system using a 15N-2.2P-12.4K fertilizer (Jack&#x2019;s Professional<sup>&#xae;</sup> LX 15-5&#x2013;15 Cal-Mg LX; JR Peters, Allentown, PA, USA) at 100 mg&#xb7;L<sup>-1</sup> N. The average environmental conditions were a temperature of 23.7 &#xb1; 0.2 &#xb0;C, vapor pressure deficit (VPD) of 1.5 &#xb1; 0.2 kPa, and CO<sub>2</sub> concentration of 814.2 &#xb1; 28.7 &#x3bc;mol&#xb7;mol<sup>-1</sup> (mean &#xb1; standard deviation).</p>
<p>At 3 weeks after seeding, the plants with 6&#x2013;8 true leaves were transferred to an experimental growth chamber (E15; Conviron, Winnipeg, Manitoba, Canada) under ambient CO<sub>2</sub> and hand-watered daily with the same nutrient solution. The chamber was equipped with six 200-W white LED bars (Rev-2: GrowRay, Boulder, CO, USA) with 50% red, 20% green, 24% blue, and 6% far-red, mounted 40&#xa0;cm above the canopy. Spectral distributions were verified using a spectrometer (LI-180; LI-COR Biosciences, Lincoln, NE, USA). The lighting operated from 0:00 to 16:00 (16&#xa0;h).</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>CF measurement</title>
<p>CF was measured on the same uppermost fully expanded leaf throughout the 7-day period to track temporal responses to treatments. A pulse-amplitude modulated (PAM) fluorometer (MINI-PAM; Heinz Walz, Effeltrich, Germany), remotely controlled by a datalogger (CR1000; Campbell Scientific, Logan, UT, USA) via an RS-232 interface, was used for <italic>in situ</italic> measurements in the growth chamber. Through serial communication, the datalogger automatically executed measurement commands, retrieved data, and calculated the fluorescence parameters (<xref ref-type="bibr" rid="B30">Nam et&#xa0;al., 2025</xref>).</p>
<p>Every 30 minutes during the 16-h photoperiod, saturating light pulses were applied to determine maximum fluorescence in light (<italic>F</italic><sub>m</sub>&#x2032;), with steady-state fluorescence (<italic>F</italic><sub>t</sub>) measured immediately beforehand. The white LED light was then briefly turned off, and a 2-second pulse of far-red light was applied to measure minimal fluorescence in light (<italic>F</italic><sub>o</sub>&#x2032;), after which white light resumed. The operating PSII efficiency (&#x3a6;<sub>PSII</sub>) was calculated as (<italic>F</italic><sub>m</sub>&#x2032; &#x2013; <italic>F</italic><sub>t</sub>)/<italic>F</italic><sub>m</sub>&#x2032; (<xref ref-type="bibr" rid="B11">Genty et&#xa0;al., 1989</xref>) to estimate the proportion of absorbed light used in photochemistry. ETR, representing the overall photosynthetic capacity, was estimated as &#x3a6;<sub>PSII</sub> &#xd7; PPFD &#xd7; 0.5 &#xd7; 0.84, assuming an equal distribution of photons between PSI and PSII and an 84% incident light absorption (<xref ref-type="bibr" rid="B25">Maxwell and Johnson, 2000</xref>).</p>
<p>Light-adapted maximum quantum efficiency (<italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032;) was calculated as (<italic>F</italic><sub>m</sub>&#x2032; &#x2013; <italic>F</italic><sub>o</sub>&#x2032;)/<italic>F</italic><sub>m</sub>&#x2032;, which represents the maximum efficiency of PSII while acclimated at a given light intensity (<xref ref-type="bibr" rid="B3">Baker et&#xa0;al., 2007</xref>). Dark-adapted parameters (<italic>F</italic><sub>o</sub> and <italic>F</italic><sub>m</sub>) were measured hourly from 16:00 to 0:00, and dark-adapted maximum efficiency of PSII (<italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub>) was calculated as (<italic>F</italic><sub>m</sub> &#x2013; <italic>F</italic><sub>o</sub>)/<italic>F</italic><sub>m</sub>. <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> measured after 1 and 8 hours of dark adaptation (<italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 1h and <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 8h) were used to assess PSII recovery, as photoprotective and photoinhibitory components of non-photochemical quenching (NPQ) relax at different rates, ranging from minutes to several hours, depending on stress severity (<xref ref-type="bibr" rid="B25">Maxwell and Johnson, 2000</xref>). Lake model-based photochemical quenching coefficient (qL) represents the fraction of PSII reaction centers that are open. Quantum yield of NPQ (&#x3a6;<sub>NPQ</sub>) and quantum yield of non-regulated energy dissipation (&#x3a6;<sub>NO</sub>) were calculated following <xref ref-type="bibr" rid="B19">Kramer et&#xa0;al. (2004)</xref>.</p>
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<p>Measurements were taken automatically by the datalogger using a proprietary software (LoggerNet v.4.7; Campbell Scientific, Logan, UT, USA). The datalogger triggered measurements of <italic>F</italic><sub>m</sub>/<italic>F</italic><sub>m</sub>&#x2032;, <italic>F</italic><sub>o</sub>/<italic>F</italic><sub>o</sub>&#x2032;, and <italic>F</italic><sub>t</sub> every 30 minutes during the photoperiod and hourly during the dark period. These raw fluorescence values were subsequently used to calculate various CF parameters. Additionally, with the integration of far-red LED light into the automated CF measurement protocol, parameters that require <italic>F</italic><sub>o</sub>&#x2032; to be calculated, such as <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032; and qL, can be obtained throughout the daytime in the presence of ambient light. Cumulative ETR was calculated by integrating instantaneous ETR values measured at 15-min intervals during the photoperiod across the entire experimental period. This metric quantifies the total photochemical electron flux processed by PSII over time and was used to evaluate the relationship between integrated photochemical activity and final shoot biomass.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Leaf photosynthesis measurements and harvest</title>
<p>Leaf gas exchange was measured on the uppermost fully expanded leaves at two days after treatment (DAT) and DAT 7 using a portable photosynthesis system (CIRAS-3; PP Systems, Amesbury, MA, USA). Net photosynthetic rate (<italic>A</italic>), stomatal conductance (<italic>g</italic><sub>s</sub>), transpiration rate (<italic>E</italic>), intercellular CO<sub>2</sub> concentration (<italic>C</italic><sub>i</sub>), and water use efficiency (WUE) were recorded under a constant CO<sub>2</sub> concentration of 400 &#x3bc;mol&#xb7;mol<sup>-1</sup>, reflecting typical ambient CO<sub>2</sub> levels for standardized measurements.</p>
<p>At DAT 7, rapid <italic>A</italic>&#x2013;<italic>C</italic><sub>i</sub> response curves were obtained using a high-speed CO<sub>2</sub> ramping technique (<xref ref-type="bibr" rid="B38">Stinziano et&#xa0;al., 2017</xref>) to assess photosynthetic capacity and identify limiting factors under experimental stress conditions. CO<sub>2</sub> concentration was ramped from 100 to 1500 &#x3bc;mol&#xb7;mol<sup>-1</sup> over 6 minutes, with baseline cuvette response established using an empty cuvette. Post-data processing was conducted to recompute actual <italic>A</italic> and <italic>C</italic><sub>i</sub> values using a spreadsheet provided by the portable photosynthesis system. Curve fitting was then performed by minimizing the residual sum of squares, as described by <xref ref-type="bibr" rid="B36">Sharkey et&#xa0;al. (2007)</xref>, to derive the maximum rate of ribulose-1,5-bisphosphate carboxylase oxygenase (Rubisco) carboxylation (<italic>V</italic><sub>c,max</sub>), the maximal rate of electron transport (<italic>J</italic><sub>max</sub>), and triose phosphate utilization (TPU). More details regarding the methodology of the rapid <italic>A</italic>/<italic>C</italic><sub>i</sub> curves can be found in <xref ref-type="bibr" rid="B31">PPSystems (2022)</xref> and <xref ref-type="bibr" rid="B20">Liu and van Iersel (2021)</xref>.</p>
<p>While gas exchange parameters at DAT 2 were directly measured under a steady CO<sub>2</sub> concentration, those at DAT 7&#xa0;were extracted from the ramping data point at 400 &#x3bc;mol&#xb7;mol<sup>-1</sup> CO<sub>2</sub>. During all gas exchange measurements, environmental conditions in the cuvette (temperature, light intensity, and humidity) were set to match the corresponding experimental conditions. Measurements were conducted between 14:00 and 16:00 to minimize the effect of the time of day.</p>
<p>All lettuce plants were harvested at DAT 7. Shoot fresh weight was measured immediately, and shoot dry weight was determined after oven-drying at 80&#xb0;C for 72 hours. Shoot water content was measured to evaluate stress-induced dehydration and morphological adaptation, and it was calculated as (shoot fresh weight &#x2013; shoot dry weight)/shoot fresh weight. Leaf chlorophyll content was measured using a handheld chlorophyll meter (CCM-220 plus; Opti-Sciences, Hudson, NH, USA) on six uppermost fully expanded leaves per plant, and the values were averaged.</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Treatments and experimental design</title>
<p>Plants were exposed to three temperatures (18, 25, and 32&#xb0;C) and two light intensities (150 and 500 &#xb5;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> PPFD) for 7 days. The temperature treatments were selected to span a physiologically relevant range for lettuce, with 25&#xa0;&#xb0;C representing near-optimal daytime conditions and 18 and 32&#xa0;&#xb0;C representing cooler and warmer conditions that may induce stress (<xref ref-type="bibr" rid="B15">Holmes et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B50">Zhou et&#xa0;al., 2022</xref>). The two PPFD levels, applied under a 16-h photoperiod, corresponded to DLI of 8.64 and 28.8 mol&#xb7;m<sup>-2</sup>&#xb7;d<sup>-1</sup>, representing typical greenhouse light conditions, within ranges where lettuce growth increases with PPFD and DLI (<xref ref-type="bibr" rid="B9">Faust and Logan, 2018</xref>; <xref ref-type="bibr" rid="B26">Mayorga-Gomez et&#xa0;al., 2024</xref>).</p>
<p>The actual average temperatures and light levels recorded across all replicates during the treatment period were 18.1 &#xb1; 1.0, 24.8 &#xb1; 0.3, and 31.9 &#xb1; 0.4&#xa0;&#xb0;C, and 150.0 &#xb1; 0.6 and 500.7 &#xb1; 2.7 &#xb5;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, respectively. Light intensity was continuously monitored using photodiodes (SLD-69C1; Silonex, Montreal, Quebec, Canada), with one sensor placed at canopy height per experimental unit. All photodiodes were calibrated against a quantum sensor (MQ-500; Apogee Instruments, Logan, UT, USA) before the experiment and connected to a datalogger for real-time monitoring and light adjustment.</p>
<p>The average VPD was 0.99 &#xb1; 0.16, 1.20 &#xb1; 0.18, and 1.21 &#xb1; 0.22&#xa0;kPa, and the corresponding relative humidity (RH) values were 52.7% &#xb1; 5.4%, 61.6% &#xb1; 5.7%, and 74.5% &#xb1; 4.4% at 18, 25, and 32&#xb0;C, respectively. In the growth chamber, humidity was controlled to balance VPD among temperature treatments. At 32&#xb0;C, humidifiers (Classic 300S Ultrasonic Smart Humidifier; Levoit, Anaheim, CA, USA) were used to maintain approximately 75% RH, whereas at 18&#xb0;C, two dehumidifiers (800 sq ft dehumidifier; Gocheer, Shenzhen, China) operated at full capacity to reduce RH and increase VPD, although values above ~ 1.2 kPa could not be achieved.</p>
<p>The experiment was arranged as a split-plot randomized complete block design (RCBD) conducted over 12 weeks in a single growth chamber. Due to spatial limitations, blocks were arranged temporally, with each 3-week period considered one block and the sequence repeated four times, resulting in a total of 12 weeks. Temperature (whole-plot factor) was randomly assigned weekly to each experimental unit (7-day period) within each block (n = 4). A reflective partition divided the chamber into two sections (left and right) for the light treatments (split-plot factor), with 150 and 500 &#xb5;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> PPFD applied at each light intensity randomly within each temperature condition. The temperature was uniform across the chamber during the experimental period.</p>
</sec>
<sec id="s2_6">
<label>2.6</label>
<title>Statistical analysis</title>
<p>All statistical analyses were conducted in statistical software (R version 4.5.0; R Foundation for Statistical Computing, Vienna, Austria). Linear mixed-effects models were used for all analyses, with experimental block included as a random effect. For CF parameters, three-way analysis of variance (ANOVA) was performed with temperature, PPFD, and DAT as fixed factors. The fixed-effects structure of the model was y<sub>ijkl</sub> = &#xb5; + T<sub>i</sub> + P<sub>j</sub> + D<sub>k</sub> + (TP)<sub>ij</sub> + (TD)<sub>ik</sub> + (PD)<sub>jk</sub> + (TPD)<sub>ijk</sub> + b<sub>l</sub> + &#x3f5;<sub>ijkl</sub>, where T, P, and D represent the effects of temperature, PPFD, and DAT effect, respectively, b<sub>l</sub> represents the random effect of experimental block, and &#x3f5;<sub>ijkl</sub> is the residual error. Because CF parameters were measured repeatedly over time, a continuous autoregressive correlation structure (corCAR1) was used to account for temporal autocorrelation among observations. Variance weighting was also applied to address heteroscedasticity observed across temperature and PPFD treatments. Model structures were evaluated sequentially, and autocorrelation functions (ACF) of normalized residuals were used to confirm that temporal autocorrelation was adequately accounted for without introducing unnecessary model complexity. For gas exchange, <italic>A</italic>/<italic>C</italic><sub>i</sub> curve, and harvest parameters, two-way ANOVA was conducted with temperature and PPFD as fixed factors. Pairwise comparisons were performed using Tukey&#x2019;s Honestly Significant Difference (HSD) test at a 95% confidence level. For the correlation between ETR and <italic>A</italic>, linear models were constructed that included interaction terms of ETR with temperature, DAT, and the interaction of temperature &#xd7; DAT to test how these factors influenced the slope of the <italic>A</italic>&#x2013;ETR relationship. Model assumptions were evaluated using residual diagnosis, including residual-fitted plots and quantile-quantile plots, to confirm homoscedasticity and normality of residuals.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Real-time monitoring of photochemical activities</title>
<p>A real-time CF monitoring system (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>) was used to collect high-temporal-resolution data on photochemical activity every 30 minutes during the photoperiod and every hour at night. This setup enabled continuous monitoring of CF over a 7-day period, capturing both daily and within-day changes under different temperature and light conditions (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2</bold></xref>). &#x3a6;<sub>PSII</sub> gradually increased during the daytime within each day, particularly under 32&#xb0;C with low light and under high light (500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> PPFD) across all temperatures, suggesting short-term photochemical adjustments to heat and light stress (<xref ref-type="fig" rid="f2"><bold>Figures&#xa0;2A, B</bold></xref>). These diurnal changes were associated with a diurnal decrease in &#x3a6;<sub>NPQ</sub> and &#x3a6;<sub>NO</sub>, reflecting a shift in energy distribution from non-photochemical to photochemical processes (<xref ref-type="fig" rid="f2"><bold>Figures&#xa0;2E&#x2013;H</bold></xref>). Notably, a distinct zigzag pattern in &#x3a6;<sub>PSII</sub> was observed under 32&#xb0;C and 150 &#x3bc;mol&#xb7;m<sup>&#x2212;2</sup>&#xb7;s<sup>&#x2212;1</sup> PPFD, characterized by a daytime increase followed by an abrupt decrease the next morning, leading to an overall decline from DAT 2 to 7. In contrast, plants under 500 &#x3bc;mol&#xb7;m<sup>&#x2212;2</sup>&#xb7;s<sup>&#x2212;1</sup> PPFD showed a more continuous increase in &#x3a6;<sub>PSII</sub>, with minimal discrepancies between days.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Schematic of the real-time chlorophyll fluorescence (CF) monitoring system installed in a growth chamber. The data logger communicates with the chlorophyll fluorometer via serial communication to send measurement commands at specified intervals and receive real-time CF data. White light emitting diodes (LEDs) provide actinic light for plant growth. During each CF measurement cycle, the white LEDs are temporarily turned off, and far-red LEDs activate for a few seconds to allow measurement of minimal fluorescence. After the measurement, actinic lighting resumes.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-17-1733839-g001.tif">
<alt-text content-type="machine-generated">A diagram of a growing facility showing the process of collecting chlorophyll fluorescence data. A plant is illuminated by white LEDs. A datalogger sends measurement commands to collect fluorescence data. A chlorophyll fluorometer measures fluorescence and communicates with the datalogger every fifteen minutes. A quantum sensor is also involved in the setup.</alt-text>
</graphic></fig>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Chlorophyll fluorescence parameters were measured every 30 minutes during a 16-hour photoperiod in lettuce (<italic>Lactuca sativa</italic> &#x2018;Green Towers&#x2019;) grown under two photosynthetic photon flux densities (PPFD) (150 and 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>) and three temperature conditions (18, 25, and 32&#xa0;&#xb0;C) for seven days. Data were collected for the operating photosystem II (PSII) efficiency (&#x3a6;<sub>PSII</sub>) <bold>(A, B)</bold>, electron transport rate (ETR) <bold>(C, D)</bold>, quantum yield of non-photochemical quenching (&#x3a6;<sub>NPQ</sub>) <bold>(E, F)</bold>, and quantum yield of non-regulated energy dissipation (&#x3a6;<sub>NO</sub>) <bold>(G, H)</bold>. Solid lines indicate mean values, and shaded areas indicate standard errors (n = 4). Some standard error areas are not visible due to their minimal size.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-17-1733839-g002.tif">
<alt-text content-type="machine-generated">Graphical representation with eight panels comparing photochemical responses under different light intensities and temperatures over time. Panels A, C, E, G correspond to 150 micromoles per square meter per second and panels B, D, F, H to 500 micromoles per square meter per second. Variables are measured over seven days after treatment, displaying different trends for temperatures 18&#xb0;C, 25&#xb0;C, and 32&#xb0;C using blue, green, and red lines respectively, with metrics including &#x3a6;PSII, ETR, &#x3a6;NPQ, and &#x3a6;NO.</alt-text>
</graphic></fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Photosynthetic efficiency and energy dissipation</title>
<p>Overall, &#x3a6;<sub>PSII</sub> was lower under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> than under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, and there was no temperature effect alone (<xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>), but the temperature effect varied depending on PPFD (<xref ref-type="fig" rid="f2"><bold>Figures&#xa0;2A, B</bold></xref>). At 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, &#x3a6;<sub>PSII</sub> was lowest at 32&#xb0;C, whereas at 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, it was lowest at 18&#xb0;C. Across all conditions, 25&#xb0;C consistently showed the highest &#x3a6;<sub>PSII</sub>, indicating that specific combinations of light intensity and temperature could be suboptimal for maintaining photochemical efficiency in lettuce. Although &#x3a6;<sub>PSII</sub> tended to decrease at extreme temperatures, these differences were not statistically significant when averaged across time (<xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3A</bold></xref>).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Effects of temperature, photosynthetic photon flux density (PPFD), and days after treatment (DAT) on daily averaged chlorophyll fluorescence parameters; operating photosystem II (PSII) efficiency (&#x3a6;<sub>PSII</sub>), electron transport rate (ETR), quantum yield of non-photochemical quenching (&#x3a6;<sub>NPQ</sub>), quantum yield of non-regulated energy dissipation (&#x3a6;<sub>NO</sub>), light-adapted maximum quantum efficiency (<italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032;), 1-hour dark-adapted maximum quantum efficiency (<italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 1h), 8-hour dark-adapted maximum quantum efficiency (<italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 8h), and photochemical quenching coefficient (qL).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center" colspan="2">Treatments</th>
<th valign="middle" align="center">&#x3a6;<sub>PSII</sub></th>
<th valign="middle" align="center">ETR</th>
<th valign="middle" align="center">&#x3a6;<sub>NPQ</sub></th>
<th valign="middle" align="center">&#x3a6;<sub>NO</sub></th>
<th valign="middle" align="center"><italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032;</th>
<th valign="middle" align="center"><italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 1h</th>
<th valign="middle" align="center"><italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 8h</th>
<th valign="middle" align="center">qL</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="3" align="left">Temperature (T)</td>
<td valign="middle" align="left">18&#xa0;&#xb0;C</td>
<td valign="middle" align="center">0.670 &#xb1; 0.011 a</td>
<td valign="middle" align="center">87.5 &#xb1; 2.3 a</td>
<td valign="middle" align="center">0.109 &#xb1; 0.006</td>
<td valign="middle" align="center">0.221 &#xb1; 0.006 a</td>
<td valign="middle" align="center">0.748 &#xb1; 0.003 a</td>
<td valign="middle" align="center">0.753 &#xb1; 0.006 b</td>
<td valign="middle" align="center">0.820 &#xb1; 0.003 ab</td>
<td valign="middle" align="center">0.707 &#xb1; 0.022 b</td>
</tr>
<tr>
<td valign="middle" align="left">25&#xa0;&#xb0;C</td>
<td valign="middle" align="center">0.695 &#xb1; 0.003 a</td>
<td valign="middle" align="center">91.8 &#xb1; 0.8 a</td>
<td valign="middle" align="center">0.114 &#xb1; 0.003</td>
<td valign="middle" align="center">0.191 &#xb1; 0.005 b</td>
<td valign="middle" align="center">0.740 &#xb1; 0.003 a</td>
<td valign="middle" align="center">0.776 &#xb1; 0.003 a</td>
<td valign="middle" align="center">0.831 &#xb1; 0.001 a</td>
<td valign="middle" align="center">0.806 &#xb1; 0.031 ab</td>
</tr>
<tr>
<td valign="middle" align="left">32&#xa0;&#xb0;C</td>
<td valign="middle" align="center">0.680 &#xb1; 0.005 a</td>
<td valign="middle" align="center">91.3 &#xb1; 0.8 a</td>
<td valign="middle" align="center">0.124 &#xb1; 0.004</td>
<td valign="middle" align="center">0.195 &#xb1; 0.002 b</td>
<td valign="middle" align="center">0.714 &#xb1; 0.003 b</td>
<td valign="middle" align="center">0.757 &#xb1; 0.003 ab</td>
<td valign="middle" align="center">0.813 &#xb1; 0.002 b</td>
<td valign="middle" align="center">0.869 &#xb1; 0.009 a</td>
</tr>
<tr>
<td valign="middle" rowspan="2" align="left">PPFD (P)</td>
<td valign="middle" align="left">150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup></td>
<td valign="middle" align="center">0.722 &#xb1; 0.002 a</td>
<td valign="middle" align="center">45.5 &#xb1; 0.1 b</td>
<td valign="middle" align="center">0.086 &#xb1; 0.003 b</td>
<td valign="middle" align="center">0.193 &#xb1; 0.003 b</td>
<td valign="middle" align="center">0.747 &#xb1; 0.002 a</td>
<td valign="middle" align="center">0.778 &#xb1; 0.003 a</td>
<td valign="middle" align="center">0.820 &#xb1; 0.003 a</td>
<td valign="middle" align="center">0.874 &#xb1; 0.011 a</td>
</tr>
<tr>
<td valign="middle" align="left">500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup></td>
<td valign="middle" align="center">0.642 &#xb1; 0.004 b</td>
<td valign="middle" align="center">134.9 &#xb1; 0.9 a</td>
<td valign="middle" align="center">0.146 &#xb1; 0.003 a</td>
<td valign="middle" align="center">0.212 &#xb1; 0.002 a</td>
<td valign="middle" align="center">0.721 &#xb1; 0.001 b</td>
<td valign="middle" align="center">0.746 &#xb1; 0.002 b</td>
<td valign="middle" align="center">0.823 &#xb1; 0.001 a</td>
<td valign="middle" align="center">0.714 &#xb1; 0.010 b</td>
</tr>
<tr>
<th valign="middle" colspan="10" align="left"><italic>P</italic>-values</th>
</tr>
<tr>
<td valign="middle" rowspan="7" align="left"/>
<td valign="middle" align="left"><italic>T</italic></td>
<td valign="middle" align="center"><italic>0.025</italic></td>
<td valign="middle" align="center"><italic>0.019</italic></td>
<td valign="middle" align="center"><italic>0.61</italic></td>
<td valign="middle" align="center"><italic>0.028</italic></td>
<td valign="middle" align="center"><italic>0.014</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.0078</italic></td>
<td valign="middle" align="center"><italic>0.016</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>P</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.0054</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>DAT</italic></td>
<td valign="middle" align="center"><italic>0.49</italic></td>
<td valign="middle" align="center"><italic>0.50</italic></td>
<td valign="middle" align="center"><italic>0.78</italic></td>
<td valign="middle" align="center"><italic>0.33</italic></td>
<td valign="middle" align="center"><italic>0.94</italic></td>
<td valign="middle" align="center"><italic>0.76</italic></td>
<td valign="middle" align="center"><italic>0.013</italic></td>
<td valign="middle" align="center"><italic>0.26</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>T &#xd7; P</italic></td>
<td valign="middle" align="center"><italic>0.037</italic></td>
<td valign="middle" align="center"><italic>0.0013</italic></td>
<td valign="middle" align="center"><italic>0.29</italic></td>
<td valign="middle" align="center"><italic>0.30</italic></td>
<td valign="middle" align="center"><italic>0.034</italic></td>
<td valign="middle" align="center"><italic>0.17</italic></td>
<td valign="middle" align="center"><italic>0.070</italic></td>
<td valign="middle" align="center"><italic>0.75</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>T &#xd7; DAT</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.0037</italic></td>
<td valign="middle" align="center"><italic>0.13</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.010</italic></td>
<td valign="middle" align="center"><italic>0.97</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>P &#xd7; DAT</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.0076</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>T &#xd7; P &#xd7; DAT</italic></td>
<td valign="middle" align="center"><italic>0.88</italic></td>
<td valign="middle" align="center"><italic>0.079</italic></td>
<td valign="middle" align="center"><italic>0.74</italic></td>
<td valign="middle" align="center"><italic>0.83</italic></td>
<td valign="middle" align="center"><italic>0.67</italic></td>
<td valign="middle" align="center"><italic>0.58</italic></td>
<td valign="middle" align="center"><italic>0.95</italic></td>
<td valign="middle" align="center"><italic>0.60</italic></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Values are means &#xb1; standard error (n = 4), and different letters within a column from the same factor indicate significant differences at &#x3b1; = 0.05, according to Tukey&#x2019;s Honestly Significant Difference (HSD) test.</p></fn>
</table-wrap-foot>
</table-wrap>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Chlorophyll fluorescence parameters for temperature &#xd7; photosynthetic photon flux density (PPFD) interactions were statistically significant. Data represent means of operating photosystem II (PSII) efficiency (&#x3a6;<sub>PSII</sub>) <bold>(A)</bold>, electron transport rate (ETR) <bold>(B)</bold>, and light-adapted maximum quantum efficiency (<italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032;) <bold>(C)</bold>, averaged across days after treatment. Different letters indicate significant differences (<italic>P</italic>&#xa0;&lt;&#xa0;0.05) based on Tukey&#x2019;s Honestly Significant Difference (HSD) test. Error bars represent standard errors (n = 4).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-17-1733839-g003.tif">
<alt-text content-type="machine-generated">Bar graphs illustrating the interactive effects of temperature and light intensity on three parameters: (A) &#x3a6;PSII, (B) ETR, and (C) Fv'/Fm', with significance levels (P-values): 0.037, 0.0013, and 0.034 respectively. Temperature conditions are 18&#xb0;C (blue), 25&#xb0;C (green), and 32&#xb0;C (red), and light intensity conditions are 150 and 500 &#x3bc;mol m^-2 s^-1. Each graph shows distinct groupings marked by letters to indicate statistical differences. Error bars represent variability.</alt-text>
</graphic></fig>
<p>Daily means of CF values were calculated to assess the effects of temperature, light intensity, and DAT, as the 30-minute interval data showed high autocorrelation and were difficult to analyze directly (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4</bold></xref>). &#x3a6;<sub>PSII</sub> was also affected by DAT, with trends depending on both temperature and PPFD. At 25 and 32&#xb0;C, &#x3a6;<sub>PSII</sub> remained relatively constant over time, while values at 18&#xb0;C increased by approximately 10%, suggesting a recovery response (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4A</bold></xref>). Under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> PPFD, &#x3a6;<sub>PSII</sub> gradually increased by about 14% over the 7-day period, while under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, it decreased slightly by less than 4% (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4B</bold></xref>). Initially, &#x3a6;<sub>PSII</sub> under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> was 24% higher than under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, but the difference narrowed to only 5% by the end of the experiment. This suggests that plants showed the most pronounced acclimation over time in photosynthetic efficiency under high light and low temperature.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Daily mean values of chlorophyll fluorescence parameters measured over seven days after treatment (DAT). Parameters include operating photosystem II (PSII) efficiency (&#x3a6;<sub>PSII</sub>) <bold>(A, B)</bold>, electron transport rate (ETR) <bold>(C, D)</bold>, quantum yield of non-photochemical quenching (&#x3a6;<sub>NPQ</sub>) <bold>(E, F)</bold>, and quantum yield of non-regulated energy dissipation (&#x3a6;<sub>NO</sub>) <bold>(G, H)</bold>. Left panels <bold>(A, C, E, G)</bold> show temperature &#xd7; DAT interactions averaged across photosynthetic photon flux density (PPFD) levels; right panels <bold>(B, D, F, H)</bold> show PPFD &#xd7; DAT interactions averaged across temperature levels. Asterisks indicate significant differences between treatments at each time point (<italic>P</italic>&#xa0;&lt;&#xa0;0.05). Error bars represent standard errors (n = 4).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-17-1733839-g004.tif">
<alt-text content-type="machine-generated">Eight line graphs comparing the effects of temperature and photosynthetic photon flux density (PPFD) on four parameters (&#x3a6;PSII, ETR, &#x3a6;NPQ, and &#x3a6;NO) over seven days after treatment. Panels A, C, E, and G show results for three temperatures: 18&#xb0;C, 25&#xb0;C, and 32&#xb0; C. Panels B, D, F, and H show results for two PPFD levels: 150 and 500 &#x3bc;mol m&#x207b;&#xb2; s&#x207b;&#xb9;. Graphs indicate parameter changes over time with statistical significance noted. Each parameter has different trends based on temperature and PPFD variations.</alt-text>
</graphic></fig>
<p>ETR was approximately three times higher under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> compared to 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, with average values of approximately 134 and 45 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, respectively (<xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>). Compared to &#x3a6;<sub>PSII</sub>, the effects of temperature and DAT on ETR were relatively minor (<xref ref-type="fig" rid="f3"><bold>Figures&#xa0;3B</bold></xref>, <xref ref-type="fig" rid="f4"><bold>4C</bold></xref>), but followed the same overall pattern of &#x3a6;<sub>PSII</sub>, as ETR is calculated from &#x3a6;<sub>PSII</sub>, incident PPFD, and fixed coefficients.</p>
<p>&#x3a6;<sub>NPQ</sub> and &#x3a6;<sub>NO</sub> represent the proportion of absorbed light dissipated as heat or lost through unregulated pathways rather than being used for photochemistry. Both parameters were significantly higher under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> compared to 150&#xa0;&#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, indicating that higher light intensity increased non-photochemical energy dissipation, which was associated with reduced photosynthetic efficiency (<xref ref-type="fig" rid="f4"><bold>Figures&#xa0;4F, H</bold></xref>).</p>
<p>Over time, &#x3a6;<sub>NPQ</sub> and &#x3a6;<sub>NO</sub> decreased under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, corresponding with a gradual increase in &#x3a6;<sub>PSII</sub>, suggesting acclimation to high light. In contrast, under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, &#x3a6;<sub>NPQ</sub> and &#x3a6;<sub>NO</sub> remained stable, resulting in stable &#x3a6;<sub>PSII</sub>. Temporal trends differed between the two parameters. Under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, &#x3a6;<sub>NPQ</sub> exhibited a significant decrease during the first day and remained stable thereafter (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4F</bold></xref>), while &#x3a6;<sub>NO</sub> gradually decreased throughout the experiment (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4H</bold></xref>). As a result, by the end of the 7-day period, there was no significant difference in &#x3a6;<sub>NO</sub> between the two light conditions. Temperature effects on &#x3a6;<sub>NPQ</sub> over time were not clearly distinct, but at the end of the experiment, &#x3a6;<sub>NPQ</sub> was highest at 32&#xb0;C, followed by 25 and 18&#xb0;C (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4E</bold></xref>). In contrast, &#x3a6;<sub>NO</sub> remained highest at 18&#xb0;C throughout most of the experiment period, though differences among temperatures were no longer significant by DAT 6 and 7.</p>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Temporal changes in maximum quantum efficiency</title>
<p>Daily mean values of <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032;, an estimate of maximum quantum efficiency at a given light intensity if all PSII centers were open, showed a different trend compared to &#x3a6;<sub>PSII</sub>. <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032; was higher under 150 than 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, but gradually decreased over time, whereas it remained relatively stable under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5B</bold></xref>). Temperature effects were also observed: <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032; was highest at 18&#xb0;C, followed by 25 and 32&#xb0;C under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> (<xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3C</bold></xref>), with increasing values at 18&#xa0;&#xb0;C and decreasing trends at 25 and 32&#xb0;C (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5A</bold></xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Daily mean values of chlorophyll fluorescence parameters measured over seven days after treatment (DAT). Parameters include light-adapted maximum quantum efficiency (<italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032;) <bold>(A, B)</bold>, 1-hour dark-adapted <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> (<italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 1h) <bold>(C, D)</bold>, 8-hour dark-adapted <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> (<italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 8h) <bold>(E, F)</bold>, and photochemical quenching coefficient (qL) <bold>(G, H)</bold>. Left panels <bold>(A, C, E, G)</bold> show temperature &#xd7; DAT interactions averaged across photosynthetic photon flux density (PPFD) levels; right panels <bold>(B, D, F, H)</bold> show PPFD &#xd7; DAT interactions averaged across temperature levels. Asterisks indicate significant differences between treatments at each time point (<italic>P</italic>&#xa0;&lt;&#xa0;0.05). Error bars represent standard errors (n = 4).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-17-1733839-g005.tif">
<alt-text content-type="machine-generated">Eight line graphs comparing the effects of temperature and photosynthetic photon flux density (PPFD) on four parameters (Fv'/Fm', Fv/Fm at 1 hour and 8 hours, and qL) over seven days after treatment. Panels A, C, E, and G show results for three temperatures: 18&#xb0;C, 25&#xb0;C, and 32&#xb0; C. Panels B, D, F, and H show results for two PPFD levels: 150 and 500 &#x3bc;mol m&#x207b;&#xb2; s&#x207b;&#xb9;. Graphs indicate parameter changes over time with statistical significance noted. Each parameter has different trends based on temperature and PPFD variations.</alt-text>
</graphic></fig>
<p>The average <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> across all treatments and DAT was 0.762 after 1 hour of dark adaptation, but stabilized at 0.821 from 2 through 8 hours after dark adaptation, indicating that full recovery was reached within the initial two hours. Therefore, <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 1h and <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 8h were selected to assess transient and sustained effects of environmental stress. Under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> decreased over time, while it increased under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> (<xref ref-type="fig" rid="f5"><bold>Figures&#xa0;5D, F</bold></xref>). <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 1h was consistently higher under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, but <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 8h under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> recovered fully, approaching 0.83, the commonly accepted optimal value. <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 1h and <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 8h were highest at 25&#xb0;C and lower under suboptimal temperatures (<xref ref-type="fig" rid="f5"><bold>Figures&#xa0;5C, E</bold></xref>). However, <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 8h at 18&#xb0;C recovered to approximately 0.83 by DAT 6 and 7, while values at 32&#xb0;C remained low around 0.813, suggesting more persistent stress at higher temperatures despite a sufficient dark adaptation period.</p>
<p>qL, the proportion of open PSII reaction centers, also showed clear temperature and light effects. qL was highest at 32&#xb0;C, followed by 25 and 18&#xb0;C, and these temperature-dependent differences remained nearly constant throughout the experiment (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5G</bold></xref>). Under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, qL remained stable, whereas it gradually increased under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5H</bold></xref>). Consequently, the large initial difference between light intensities diminished by DAT 3.</p>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Leaf gas exchange parameters</title>
<p>leaf gas exchange measurements were conducted to examine whether the effects of temperature and light intensity observed in CF were also reflected in CO<sub>2</sub> assimilation and stomatal responses. Measurements were taken on DAT 2 and 7 to capture both early stress responses and potential acclimation (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6</bold></xref>).The <italic>A</italic> was consistently higher at 500 than under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> at both time points, regardless of temperature (<xref ref-type="fig" rid="f6"><bold>Figures&#xa0;6A, B</bold></xref>). However, temperature effects varied depending on light intensity and time. Under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, temperature differences were minimal. In contrast, under 500&#xa0;&#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, <italic>A</italic> was lowest at 32&#xb0;C on DAT 2 but became highest on DAT 7, indicating recovery or acclimation at high temperature.</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Leaf gas exchange parameters measured at two days <bold>(A, C, E)</bold> and seven days <bold>(B, D, F, G)</bold> after treatment. Shown are parameters for which temperature &#xd7; photosynthetic photon flux density (PPFD) interactions were statistically significant: photosynthetic rate (<italic>A</italic>) <bold>(A, B)</bold>, water use efficiency (WUE) <bold>(C, D)</bold>, intercellular carbon dioxide (CO<sub>2</sub>) concentration (<italic>C</italic><sub>i</sub>) <bold>(E)</bold>, stomatal conductance (<italic>g</italic><sub>s</sub>) <bold>(F)</bold>, and transpiration rate (<italic>E</italic>) <bold>(G)</bold>. Different letters denote significant differences based on Tukey&#x2019;s Honestly Significant Difference (HSD) test. (<italic>P</italic>&#xa0;&lt;&#xa0;0.05). Error bars represent standard error (n = 4).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-17-1733839-g006.tif">
<alt-text content-type="machine-generated">Bar charts showing leaf gas exchange responses to three temperatures (18&#xb0;C, 25&#xb0;C, 32&#xb0;C) and two light intensities (150 and 500 &#x3bc;mol m&#x207b;&#xb2; s&#x207b;&#xb9;) over two time points, days after treatment 2 and 7. Variables include photosynthetic rate (A), water use efficiency (WUE), intercellular CO2 concentration (Ci), stomatal conductance (gs), and transpiration rate (E). Statistically significant differences are indicated, with P-values and letters denoting statistical groups. Error bars represent variability.</alt-text>
</graphic></fig>
<p><italic>g</italic><sub>s</sub> increased with temperature on DAT 2, with no significant effect of PPFD (<xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref>). By DAT 7, under 32&#xb0;C and 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, the <italic>g</italic><sub>s</sub> increased by 900 mmol&#xb7;H<sub>2</sub>O&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> and was 5.6 times higher than in other treatment combinations (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6F</bold></xref>). These results indicate strong stomatal adjustment under combined high temperature and high light over time. <italic>E</italic> followed a similar pattern to <italic>g</italic><sub>s</sub>, increasing with temperature across both DATs and PPFD levels. In particular, at DAT 7 under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, the <italic>E</italic> was 5.3 times higher at 32&#xb0;C compared to the lower temperatures (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6G</bold></xref>). On both DAT 2 and 7, <italic>C</italic><sub>i</sub> was lower under 500 than under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, and 32&#xa0;&#xb0;C had the highest <italic>C</italic><sub>i</sub> across temperature treatments (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6E</bold></xref>). The overall mean <italic>C</italic><sub>i</sub> decreased from 314 to 231 &#xb5;mol&#xb7;mol<sup>-1</sup> from DAT 2 to DAT 7. WUE declined with increasing temperature on both dates, with consistently higher values under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>. The temperature effect on WUE was more pronounced under high light, while differences under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> were not statistically significant (<xref ref-type="fig" rid="f6"><bold>Figures&#xa0;6C, D</bold></xref>) (<italic>P</italic> &gt; 0.05).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Effects of temperature and photosynthetic photon flux density (PPFD) on leaf photosynthesis parameters; Photosynthetic rate (<italic>A</italic>), stomatal conductance (<italic>g</italic><sub>s</sub>), transpiration rate (<italic>E</italic>), intercellular carbon dioxide (CO<sub>2</sub>) concentration (<italic>C</italic><sub>i</sub>), and water use efficiency (WUE). Measurements were taken on days after treatment (DAT) 2 and 7, and the data were analyzed separately for each day.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">DAT</th>
<th valign="middle" align="center" colspan="2">Treatments</th>
<th valign="middle" align="center"><italic>A</italic> (&#x3bc;mol&#xb7;CO<sub>2</sub>&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>)</th>
<th valign="middle" align="center"><italic>g</italic><sub>s</sub> (mol&#xb7;H<sub>2</sub>O&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>)</th>
<th valign="middle" align="center"><italic>E</italic> (mmol&#xb7;H<sub>2</sub>O&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>)</th>
<th valign="middle" align="center"><italic>C</italic><sub>i</sub> (&#x3bc;mol&#xb7;mol<sup>-1</sup>)</th>
<th valign="middle" align="center">WUE (&#x3bc;mol&#xb7;CO<sub>2</sub>&#xb7; mmol<sup>-1</sup>&#xb7;H<sub>2</sub>O)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="9" align="left">DAT 2</td>
<td valign="middle" rowspan="3" align="left">Temperature (T)</td>
<td valign="middle" align="left">18&#xa0;&#xb0;C</td>
<td valign="middle" align="center">9.30 &#xb1; 0.22 a</td>
<td valign="middle" align="center">145 &#xb1; 6 b</td>
<td valign="middle" align="center">2.72 &#xb1; 0.20 b</td>
<td valign="middle" align="center">290 &#xb1; 6 b</td>
<td valign="middle" align="center">3.55 &#xb1; 0.16 a</td>
</tr>
<tr>
<td valign="middle" align="left">25&#xa0;&#xb0;C</td>
<td valign="middle" align="center">9.98 &#xb1; 0.42 a</td>
<td valign="middle" align="center">301 &#xb1; 40 ab</td>
<td valign="middle" align="center">3.64 &#xb1; 0.20 b</td>
<td valign="middle" align="center">310 &#xb1; 15 ab</td>
<td valign="middle" align="center">3.10 &#xb1; 0.12 a</td>
</tr>
<tr>
<td valign="middle" align="left">32&#xa0;&#xb0;C</td>
<td valign="middle" align="center">6.24 &#xb1; 0.21 b</td>
<td valign="middle" align="center">393 &#xb1; 58 a</td>
<td valign="middle" align="center">6.54 &#xb1; 0.48 a</td>
<td valign="middle" align="center">342 &#xb1; 7 a</td>
<td valign="middle" align="center">0.95 &#xb1; 0.06 b</td>
</tr>
<tr>
<td valign="middle" rowspan="2" align="left">PPFD (P)</td>
<td valign="middle" align="left">150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup></td>
<td valign="middle" align="center">4.91 &#xb1; 0.16 b</td>
<td valign="middle" align="center">280 &#xb1; 41</td>
<td valign="middle" align="center">4.34 &#xb1; 0.24</td>
<td valign="middle" align="center">342 &#xb1; 11 a</td>
<td valign="middle" align="center">1.40 &#xb1; 0.06 b</td>
</tr>
<tr>
<td valign="middle" align="left">500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup></td>
<td valign="middle" align="center">12.10 &#xb1; 0.40 a</td>
<td valign="middle" align="center">279 &#xb1; 44</td>
<td valign="middle" align="center">4.26 &#xb1; 0.27</td>
<td valign="middle" align="center">285 &#xb1; 5 b</td>
<td valign="middle" align="center">3.67 &#xb1; 0.14 a</td>
</tr>
<tr>
<th valign="middle" colspan="7" align="center"><italic>P</italic>-values</th>
</tr>
<tr>
<td valign="middle" rowspan="3" align="left"/>
<td valign="middle" align="left"><italic>T</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>P</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.99</italic></td>
<td valign="middle" align="center"><italic>0.84</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>T &#xd7; P</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.17</italic></td>
<td valign="middle" align="center"><italic>0.24</italic></td>
<td valign="middle" align="center"><italic>0.012</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
<tr>
<td valign="middle" rowspan="9" align="left">DAT 7</td>
<td valign="middle" rowspan="3" align="left">Temperature (T)</td>
<td valign="middle" align="left">18&#xa0;&#xb0;C</td>
<td valign="middle" align="center">8.10 &#xb1; 0.40 b</td>
<td valign="middle" align="center">150 &#xb1; 21 b</td>
<td valign="middle" align="center">1.41 &#xb1; 0.16 b</td>
<td valign="middle" align="center">223 &#xb1; 12 b</td>
<td valign="middle" align="center">6.10 &#xb1; 0.73 a</td>
</tr>
<tr>
<td valign="middle" align="left">25&#xa0;&#xb0;C</td>
<td valign="middle" align="center">7.86 &#xb1; 0.24 b</td>
<td valign="middle" align="center">123 &#xb1; 25 b</td>
<td valign="middle" align="center">2.01 &#xb1; 0.27 b</td>
<td valign="middle" align="center">194 &#xb1; 13 b</td>
<td valign="middle" align="center">4.08 &#xb1; 0.40 a</td>
</tr>
<tr>
<td valign="middle" align="left">32&#xa0;&#xb0;C</td>
<td valign="middle" align="center">9.80 &#xb1; 0.29 a</td>
<td valign="middle" align="center">588 &#xb1; 9 a</td>
<td valign="middle" align="center">7.72 &#xb1; 0.38 a</td>
<td valign="middle" align="center">275 &#xb1; 5 a</td>
<td valign="middle" align="center">1.22 &#xb1; 0.08 b</td>
</tr>
<tr>
<td valign="middle" rowspan="2" align="left">PPFD (P)</td>
<td valign="middle" align="left">150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup></td>
<td valign="middle" align="center">4.60 &#xb1; 0.19 b</td>
<td valign="middle" align="center">174 &#xb1; 18 b</td>
<td valign="middle" align="center">2.85 &#xb1; 0.26 b</td>
<td valign="middle" align="center">256 &#xb1; 9 a</td>
<td valign="middle" align="center">2.74 &#xb1; 0.25 b</td>
</tr>
<tr>
<td valign="middle" align="left">500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup></td>
<td valign="middle" align="center">12.58 &#xb1; 0.16 a</td>
<td valign="middle" align="center">399 &#xb1; 12 a</td>
<td valign="middle" align="center">4.58 &#xb1; 0.11 a</td>
<td valign="middle" align="center">205 &#xb1; 4 b</td>
<td valign="middle" align="center">4.86 &#xb1; 0.18 a</td>
</tr>
<tr>
<th valign="middle" colspan="7" align="center"><italic>P</italic>-values</th>
</tr>
<tr>
<td valign="middle" rowspan="3" align="left"/>
<td valign="middle" align="left"><italic>T</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>P</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>T &#xd7; P</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.47</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Values are means &#xb1; standard error (n = 4). For each DAT, different letters within a column from the same factor indicate significant differences at &#x3b1; = 0.05, according to Tukey&#x2019;s Honestly Significant Difference (HSD) test.</p></fn>
</table-wrap-foot>
</table-wrap>
<p>The relationship between ETR and <italic>A</italic> was significantly affected by temperature (<italic>P</italic> &lt;&#xa0;0.001) and the interaction between temperature and DAT (<italic>P</italic>&#xa0;&lt;&#xa0;0.001), but not by DAT alone (<italic>P</italic>&#xa0;=&#xa0;0.31). Here, the slope of the ETR-<italic>A</italic> relationship reflects the efficiency with which electrons derived from the photosynthetic electron transport chain are utilized for carbon assimilation (<xref ref-type="fig" rid="f7"><bold>Figure&#xa0;7</bold></xref>). At DAT 2, the slope was lowest at 32&#xb0;C, indicating reduced CO<sub>2</sub> assimilation per unit of electron transport at high temperature. By DAT 7, the slope at 32&#xb0;C increased and exceeded those at 18 and 25&#xb0;C, while the slopes at 18 and 25&#xb0;C decreased over time. These results suggest that the coupling between electron transport and CO<sub>2</sub> fixation was initially suppressed at high temperature but improved with acclimation.</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Relationship between photosynthetic rate (<italic>A</italic>) and electron transport rate (ETR) measured on days after treatment (DAT) 2 and 7. Each data point represents an individual replicate (n = 4) from each treatment combination. A linear regression model was used to assess the effect of ETR on <italic>A</italic> as influenced by temperature and DAT. Solid lines with circles indicate DAT 2, while dashed lines with triangles indicate DAT 7.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-17-1733839-g007.tif">
<alt-text content-type="machine-generated">Scatter plot showing the relationship between ETR (electron transport rate) and A (photosynthetic rate) at different temperatures (18&#xb0;C, 25&#xb0;C, 32&#xb0;C) and DAT (days after treatment) values (2, 7). Data points and trend lines show a significant interaction with a p-value less than 0.001.</alt-text>
</graphic></fig>
<p><italic>A</italic>/<italic>C</italic><sub>i</sub> response curves were used to illustrate photosynthetic responses across treatments (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure&#xa0;1</bold></xref>). Overall, 500&#xa0;&#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> resulted in greater <italic>A</italic> values across the <italic>C</italic><sub>i</sub> range. Temperature had no significant main effect on <italic>A</italic>, but a significant interaction between temperature and light intensity was observed (<italic>P</italic>&#xa0;=&#xa0;0.019), with reduced <italic>A</italic> at 32&#xb0;C under low light and at 18&#xb0;C under high light. <italic>V</italic><sub>c,max</sub>, <italic>J</italic>, and TPU were estimated from the <italic>A</italic>/<italic>C</italic><sub>i</sub> curves (<xref ref-type="table" rid="T3"><bold>Table&#xa0;3</bold></xref>). <italic>V</italic><sub>c,max</sub> was 3.8 times higher under 500 than 150 &#xb5;mol m<sup>-2</sup> s<sup>-1</sup>, but the temperature effect varied depending on light intensity (<xref ref-type="fig" rid="f8"><bold>Figure&#xa0;8</bold></xref>). Under 500 &#xb5;mol m<sup>-2</sup> s<sup>-1</sup>, <italic>V</italic><sub>c,max</sub> increased with temperature and reached its highest value at 32&#xb0;C. However, under 150 &#xb5;mol m<sup>-2</sup> s<sup>-1</sup>, <italic>V</italic><sub>c,max</sub> remained low across all temperatures <italic>J</italic> was strongly correlated with ETR (R<sup>2</sup>&#xa0;=&#xa0;0.92) and primarily influenced by light intensity, showing higher <italic>J</italic> under higher PPFD without significant temperature effects (<xref ref-type="table" rid="T3"><bold>Table&#xa0;3</bold></xref>). TPU also increased 2.9 times in response to high light intensity (<italic>P</italic>&#xa0;&lt;&#xa0;0.001), and a significant interaction was observed. TPU increased with temperature only under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> (<italic>P</italic>&#xa0;&lt;&#xa0;0.001).</p>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Effects of temperature and photosynthetic photon flux density (PPFD) on maximum rate of carboxylation (<italic>V</italic><sub>c,max</sub>), maximum electron transport rate (<italic>J</italic>), and triose phosphate utilization rate (TPU), measured on DAT 7.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center" colspan="2">Treatments</th>
<th valign="middle" align="center"><italic>V</italic><sub>c,max</sub> (&#x3bc;mol&#xb7;CO<sub>2</sub>&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>)</th>
<th valign="middle" align="center"><italic>J</italic> (&#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>)</th>
<th valign="middle" align="center">TPU (&#x3bc;mol&#xb7;CO<sub>2</sub>&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="3" align="left">Temperature (T)</td>
<td valign="middle" align="left">18&#xa0;&#xb0;C</td>
<td valign="middle" align="center">86.6 &#xb1; 5.3 b</td>
<td valign="middle" align="center">103.8 &#xb1; 5.1</td>
<td valign="middle" align="center">4.63 &#xb1; 0.21</td>
</tr>
<tr>
<td valign="middle" align="left">25&#xa0;&#xb0;C</td>
<td valign="middle" align="center">151.0 &#xb1; 13.4 a</td>
<td valign="middle" align="center">103.0 &#xb1; 3.1</td>
<td valign="middle" align="center">5.01 &#xb1; 0.12</td>
</tr>
<tr>
<td valign="middle" align="left">32&#xa0;&#xb0;C</td>
<td valign="middle" align="center">168.1 &#xb1; 8.4 a</td>
<td valign="middle" align="center">92.9 &#xb1; 4.2</td>
<td valign="middle" align="center">5.14 &#xb1; 0.18</td>
</tr>
<tr>
<td valign="middle" rowspan="2" align="left">PPFD (P)</td>
<td valign="middle" align="left">150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup></td>
<td valign="middle" align="center">56.5 &#xb1; 5.1 b</td>
<td valign="middle" align="center">51.3 &#xb1; 3.2 b</td>
<td valign="middle" align="center">2.53 &#xb1; 0.03 b</td>
</tr>
<tr>
<td valign="middle" align="left">500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup></td>
<td valign="middle" align="center">214.0 &#xb1; 10.9 a</td>
<td valign="middle" align="center">148.5 &#xb1; 5.0 a</td>
<td valign="middle" align="center">7.33 &#xb1; 0.20 a</td>
</tr>
<tr>
<th valign="middle" colspan="5" align="left"><italic>P</italic>-values</th>
</tr>
<tr>
<td valign="middle" rowspan="3" align="left"/>
<td valign="middle" align="left"><italic>T</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.18</italic></td>
<td valign="middle" align="center"><italic>0.057</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>P</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>T &#xd7; P</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.22</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Values are means &#xb1; standard error (n = 4), and different letters within a column from the same factor indicate significant differences at &#x3b1; = 0.05, according to Tukey&#x2019;s Honestly Significant Difference (HSD) test.</p></fn>
</table-wrap-foot>
</table-wrap>
<fig id="f8" position="float">
<label>Figure&#xa0;8</label>
<caption>
<p>Bar graphs of maximum rate of carboxylation (<italic>V</italic><sub>c,max</sub>) and triose phosphate utilization rate (TPU) measured on DAT 7, analyzed by two-way analysis of variance (ANOVA) to assess temperature &#xd7; photosynthetic photon flux density (PPFD) interactions. Bars represent means (n = 4), and different letters indicate significant differences among treatment combinations based on Tukey&#x2019;s Honestly Significant Difference (HSD) test (<italic>P</italic>&#xa0;&lt;&#xa0;0.05). Error bars represent standard errors.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-17-1733839-g008.tif">
<alt-text content-type="machine-generated">Bar charts comparing Vc,max (maximum rate of carboxylation) and TPU (triose phosphate utilization rate) at two different PPFD levels (150 and 500 &#x3bc;mol m&#x207b;&#xb2; s&#x207b;&#xb9;) and three temperature conditions (18, 25, 32&#xb0;C). Statistical significance indicated by different letters.</alt-text>
</graphic></fig>
</sec>
<sec id="s3_5">
<label>3.5</label>
<title>Growth responses</title>
<p>Shoot biomass was highest at 25 &#xb0;C and under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, with shoot dry weight reduced by 28% and 20% at 18&#xb0;C and 32&#xb0;C compared to 25&#xb0;C (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4</bold></xref>). Shoot dry weight increased significantly with increasing cumulative ETR (<italic>P</italic>&#xa0;&lt;&#xa0;0.001; <xref ref-type="fig" rid="f9"><bold>Figure&#xa0;9</bold></xref>). After accounting for cumulative ETR, temperature did not have a significant additional effect on shoot dry weight (<italic>P</italic>&#xa0;=&#xa0;0.592), and the relationship between cumulative ETR and shoot dry weight did not differ among temperature treatments (<italic>P</italic>&#xa0;=&#xa0;0.342). Although shoot fresh weight decreased by only 18% under 150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, shoot dry weight decreased by 40%. This discrepancy may be explained by higher shoot water content under low light. Likewise, shoot water content was also highest at the favorable temperature, 25&#xb0;C. Chlorophyll content was slightly higher under 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, with no significant effect of temperature. Although temperature &#xd7; light intensity interactions were significant for both chlorophyll content and shoot water content, the magnitudes were minimal (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure&#xa0;2</bold></xref>).</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Effects of temperature and photosynthetic photon flux density (PPFD) on shoot fresh weight, shoot dry weight, chlorophyll content, and shoot water content, measured at harvest on days after treatment (DAT) 7.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center" colspan="2">Treatments</th>
<th valign="middle" align="center">Shoot fresh weight (g)</th>
<th valign="middle" align="center">Shoot dry weight (g)</th>
<th valign="middle" align="center">Shoot water content (%)</th>
<th valign="middle" align="center">Chlorophyll content (CCI)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="3" align="left">Temperature (T)</td>
<td valign="middle" align="left">18&#xa0;&#xb0;C</td>
<td valign="middle" align="center">112.2 &#xb1; 8.4 b</td>
<td valign="middle" align="center">8.24 &#xb1; 0.56 b</td>
<td valign="middle" align="center">92.7 &#xb1; 0.3 b</td>
<td valign="middle" align="center">32.2 &#xb1; 0.4</td>
</tr>
<tr>
<td valign="middle" align="left">25&#xa0;&#xb0;C</td>
<td valign="middle" align="center">196.2 &#xb1; 9.0 a</td>
<td valign="middle" align="center">11.50 &#xb1; 0.40 a</td>
<td valign="middle" align="center">94.2 &#xb1; 0.2 a</td>
<td valign="middle" align="center">33.2 &#xb1; 2.5</td>
</tr>
<tr>
<td valign="middle" align="left">32&#xa0;&#xb0;C</td>
<td valign="middle" align="center">134.9 &#xb1; 6.3 b</td>
<td valign="middle" align="center">9.23 &#xb1; 0.52 b</td>
<td valign="middle" align="center">93.2 &#xb1; 0.2 b</td>
<td valign="middle" align="center">30.2 &#xb1; 0.7</td>
</tr>
<tr>
<td valign="middle" rowspan="2" align="left">PPFD (P)</td>
<td valign="middle" align="left">150 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup></td>
<td valign="middle" align="center">133.5 &#xb1; 6.2 b</td>
<td valign="middle" align="center">7.25 &#xb1; 0.32 b</td>
<td valign="middle" align="center">94.5 &#xb1; 0.1 a</td>
<td valign="middle" align="center">29.3 &#xb1; 1.1 b</td>
</tr>
<tr>
<td valign="middle" align="left">500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup></td>
<td valign="middle" align="center">162.0 &#xb1; 4.9 a</td>
<td valign="middle" align="center">12.06 &#xb1; 0.34 a</td>
<td valign="middle" align="center">92.3 &#xb1; 0.1 b</td>
<td valign="middle" align="center">34.4 &#xb1; 0.8 a</td>
</tr>
<tr>
<th valign="middle" colspan="6" align="left"><italic>P</italic>-values</th>
</tr>
<tr>
<td valign="middle" rowspan="3" align="left"/>
<td valign="middle" align="left"><italic>T</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>0.38</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>P</italic></td>
<td valign="middle" align="center"><italic>0.0014</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
<td valign="middle" align="center"><italic>&lt; 0.001</italic></td>
</tr>
<tr>
<td valign="middle" align="left"><italic>T &#xd7; P</italic></td>
<td valign="middle" align="center"><italic>0.10</italic></td>
<td valign="middle" align="center"><italic>0.13</italic></td>
<td valign="middle" align="center"><italic>0.031</italic></td>
<td valign="middle" align="center"><italic>0.012</italic></td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>Values are means &#xb1; standard error (n = 4), and different letters within a column from the same factor indicate significant differences at &#x3b1; = 0.05, according to Tukey&#x2019;s Honestly Significant Difference (HSD) test.</p></fn>
</table-wrap-foot>
</table-wrap>
<fig id="f9" position="float">
<label>Figure&#xa0;9</label>
<caption>
<p>Relationship between cumulative electron transport rate (ETR) and shoot dry weight. Each point represents an individual replicate (n = 4) for each treatment combination. A linear regression model was used to assess the effect of cumulative ETR on shoot dry weight and its interaction with temperature. Circles and triangles denote photosynthetic photon flux density (PPFD) of 150 and 500 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup>, respectively.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fpls-17-1733839-g009.tif">
<alt-text content-type="machine-generated">A scatter plot with lines shows shoot dry weight in grams versus cumulative ETR in moles per square meter. Data points are color-coded by temperature: 18&#xb0;C (blue), 25&#xb0;C (green), and 32&#xb0;C (red), and shaped by PPFD levels: 150 &#x3bc;mol m&#x207b;&#xb2; s&#x207b;&#xb9; (circles) and 500 &#x3bc;mol m&#x207b;&#xb2; s&#x207b;&#xb9; (triangles). The lines indicate positive correlations for each temperature.</alt-text>
</graphic></fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<sec id="s4_1">
<label>4.1</label>
<title>Light intensity effect on photochemistry</title>
<p>Although photosynthesis increases with light intensity, the photosynthetic efficiency often declines under high light due to excess excitation energy that cannot be used for electron transport and carbon fixation. This energy is instead dissipated via non-photochemical pathways, such as regulated heat dissipation (&#x3a6;<sub>NPQ</sub>) and unregulated energy loss (&#x3a6;<sub>NO</sub>). As shown in previous studies (<xref ref-type="bibr" rid="B19">Kramer et&#xa0;al., 2004</xref>), &#x3a6;<sub>NPQ</sub> increases proportionally with light intensity, whereas &#x3a6;<sub>NO</sub> remains relatively unchanged, suggesting that &#x3a6;<sub>NPQ</sub> plays a larger role in reducing photosynthetic efficiency under high light. It is consistent with our observation of elevated &#x3a6;<sub>NPQ</sub> but relatively similar &#x3a6;<sub>NO</sub> under high light conditions compared to low light (<xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>).</p>
<p>Over time, both &#x3a6;<sub>NPQ</sub> and &#x3a6;<sub>NO</sub> declined under high light, while &#x3a6;<sub>PSII</sub> increased, indicating dynamic acclimation (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4</bold></xref>). NPQ decreased rapidly and stabilized after DAT 2, which may be attributed to various physiological responses, such as fast adjustment of the NPQ component, energy-dependent quenching (qE), through lumen acidification, PSII subunit S (PsbS) activation, and the xanthophyll cycle (<xref ref-type="bibr" rid="B29">Murchie and Niyogi, 2011</xref>; <xref ref-type="bibr" rid="B52">Zuo, 2025</xref>). NPQ is a protective mechanism that safely dissipates excess light as heat, preventing photodamage caused by unregulated energy loss. Hence, moderately high NPQ under high light is not necessarily detrimental, although it reduces photosynthetic efficiency.</p>
<p>In contrast, &#x3a6;<sub>NO</sub> continuously declined throughout the week, suggesting that plants systematically adjusted the photosynthetic machinery and improved light use efficiency through processes associated with changes in light harvesting and electron transport capacity, such as reduced light-harvesting complex II (LHCII) antenna size, chloroplast repositioning, and modulation of electron transport enzymes (<xref ref-type="bibr" rid="B29">Murchie and Niyogi, 2011</xref>). The sustained increase in &#x3a6;<sub>PSII</sub> after DAT 2 appeared more closely associated with the decline in &#x3a6;<sub>NO</sub> than with changes in NPQ. This highlights that obtaining &#x3a6;<sub>NPQ</sub> and &#x3a6;<sub>NO</sub> data separately provides insights into the different types of mechanisms driving improvements in photosynthetic efficiency.</p>
<p>qL, which reflects both open PSII reaction centers and the redox state of the plastoquinone (PQ) pool, increased over time under high light, paralleling improvements in &#x3a6;<sub>PSII</sub> (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5H</bold></xref>). This recovery may result from enhanced PQ biosynthesis, which replenishes the oxidized PQ pool and facilitates electron transport, as previously reported by <xref ref-type="bibr" rid="B46">Yang et&#xa0;al. (2022)</xref>.</p>
<p><italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032; represents the theoretical maximum efficiency of PSII in the light-adapted state and declines further when severe photoinhibition or electron transport limitations occur after NPQ is saturated (<xref ref-type="bibr" rid="B3">Baker et&#xa0;al., 2007</xref>). Its stability under high light (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5B</bold></xref>) in this study suggests PSII capacity was preserved, likely due to effective NPQ regulation.</p>
<p>Determining accurate <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> requires a sufficient period of dark adaptation, however, 15&#x2013;30 minutes is commonly used. Residual qI from prolonged stress, the slowly reversible component of NPQ, can persist for several hours (<xref ref-type="bibr" rid="B39">Tietz et&#xa0;al., 2017</xref>). <xref ref-type="bibr" rid="B43">Willits and Peet (2001)</xref> emphasized that complete dark adaptation is necessary for the full oxidation of electron carriers and dissipation of the proton gradient. In our study, <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> continued to increase beyond 1&#xa0;h and stabilized after 2&#xa0;h, indicating that shorter dark periods may make it difficult to distinguish between transient and persistent stress.</p>
<p>Under high light, initial photoinhibition (<xref ref-type="fig" rid="f5"><bold>Figures&#xa0;5D, F</bold></xref>) likely resulted from pre-acclimation to 250 &#x3bc;mol&#xb7;m<sup>-2</sup>&#xb7;s<sup>-1</sup> in the walk-in growth chamber. Plants that had been previously grown under low light were more susceptible to photoinhibition even under moderate intensities (<xref ref-type="bibr" rid="B12">Gjindali and Johnson, 2023</xref>). As acclimation progressed, photochemical efficiency improved through the repair mechanism, resulting in ~ 0.83 of <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> from DAT 4. Under low light, <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> gradually declined but did not fall below 0.82, suggesting no severe photodamage. Instead, this pattern may reflect a physiological shift toward maximizing light capture (e.g., increasing antenna size), potentially at the expense of electron transport and carbon fixation capacity (<xref ref-type="bibr" rid="B12">Gjindali and Johnson, 2023</xref>).</p>
</sec>
<sec id="s4_2">
<label>4.2</label>
<title>Temperature and light combination effect on photochemistry</title>
<p>Temperature influenced photochemistry less dynamically than light intensity, yet clear stress responses were observed under suboptimal thermal conditions. Low temperature initially suppressed &#x3a6;<sub>PSII</sub>, mainly due to increased &#x3a6;<sub>NO</sub> rather than &#x3a6;<sub>NPQ</sub>, indicating excess energy loss through non-regulated pathways and photoinhibition. Over time, however, &#x3a6;<sub>PSII</sub> increased substantially as &#x3a6;<sub>NO</sub> decreased, suggesting photosynthetic acclimation. According to previous studies, such recovery under cold stress has been associated with enhanced repair and metabolic adjustments, including reduced antenna size, increased expression of the cytochrome b<sub>6</sub>f complex and Rubisco, and higher ATP synthase activity, which have been reported to improve electron transport and carbon fixation capacity (<xref ref-type="bibr" rid="B5">Bascu&#xf1;&#xe1;n-Godoy et&#xa0;al., 2012</xref>).</p>
<p>Cold stress impairs enzyme activity in the Calvin-Benson cycle and reduces thylakoid membrane fluidity, limiting electron transport and PSII function (<xref ref-type="bibr" rid="B10">Fracheboud and Leipner, 2003</xref>). Low qL values under low temperature conditions in this study may indicate an over-reduction of the PQ pool and a potential accumulation of ROS. However, during acclimation, increased qL with decreased &#x3a6;<sub>NO</sub> suggests a shift toward more efficient electron transport and reduced risk of photodamage (<xref ref-type="bibr" rid="B5">Bascu&#xf1;&#xe1;n-Godoy et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B24">Mattila et&#xa0;al., 2020</xref>). The gradual recovery of <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> under low temperature stress reflects repair of PSII components such as D1 and cytochrome b<sub>6</sub>f (<xref ref-type="bibr" rid="B5">Bascu&#xf1;&#xe1;n-Godoy et&#xa0;al., 2012</xref>; <xref ref-type="bibr" rid="B7">DeEll and Toivonen, 2003</xref>).</p>
<p>In contrast, high temperature resulted in the highest qL values but declining <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032; and <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5</bold></xref>), suggesting heat-induced inhibition of electron transport despite maintained reaction center openness (<xref ref-type="bibr" rid="B23">Mathur et&#xa0;al., 2014</xref>). Heat stress affects PQ oxidation, leading to singlet oxygen accumulation, plastoquinol degradation, and inhibition of Calvin-Benson cycle activity by Rubisco deactivation, thereby disrupting nicotinamide adenine dinucleotide phosphate (NADPH) consumption and redox balance (<xref ref-type="bibr" rid="B32">Rath et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B37">Sharkey and Zhang, 2010</xref>). These effects can reduce PSII efficiency, with a quadratic decrease in <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> as temperature increases (<xref ref-type="bibr" rid="B10">Fracheboud and Leipner, 2003</xref>; <xref ref-type="bibr" rid="B43">Willits and Peet, 2001</xref>).</p>
<p>Notably, combinations of suboptimal light and temperature amplify stress responses. Under low temperatures with high light, &#x3a6;<sub>PSII</sub> was the lowest and &#x3a6;<sub>NO</sub> was the highest, indicating photoinhibition due to excess light energy and limited photochemical capacity (<xref ref-type="fig" rid="f2"><bold>Figures&#xa0;2B, H</bold></xref>). Conversely, high temperature combined with low light also impaired photochemistry (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2A</bold></xref>). Under this condition, <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032; was particularly reduced, potentially due to limited light harvesting capacity paired with sustained thermal inhibition of photosynthesis and reduced chlorophyll content (<xref ref-type="bibr" rid="B12">Gjindali and Johnson, 2023</xref>). While high light can drive photoprotection, low light combined with high temperature reduces chlorophyll content and Calvin cycle enzyme activity, leading to further suppression of photochemical activity (<xref ref-type="bibr" rid="B50">Zhou et&#xa0;al., 2022</xref>).</p>
<p>Overall, while high temperatures had limited effects on &#x3a6;<sub>PSII</sub> in this study (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4A</bold></xref>), the observed decline in <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> 8h (~0.81) suggests moderate but persistent stress. Relatively low heat tolerance of lettuce may explain the limited recovery observed, as its acclimation capacity under heat stress is less dynamic compared to cold stress or high light acclimation (<xref ref-type="bibr" rid="B14">Hermida-Carrera et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B21">Lu et&#xa0;al., 2017</xref>).</p>
</sec>
<sec id="s4_3">
<label>4.3</label>
<title>Linking CF data to carbon assimilation and growth</title>
<p>Gas exchange partially tracked CF trends but diverged under temperature extremes. Carbon assimilation followed a parabolic temperature response, with suppression at both low and high temperatures (<xref ref-type="bibr" rid="B45">Yamori et&#xa0;al., 2014</xref>). At 18&#xa0;&#xb0;C, &#x3a6;<sub>PSII</sub> was reduced in the early stage (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4A</bold></xref>), but <italic>A</italic> remained similar to 25&#xa0;&#xb0;C (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6A</bold></xref>), and <italic>g</italic><sub>s</sub> and <italic>C</italic><sub>i</sub> showed no strong limitation (<xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref>), suggesting that photochemical inhibition at low temperature did not constrain CO<sub>2</sub> fixation. Previous studies have reported that reduced photochemistry under cold conditions can be compensated by lower dark respiration, reduced photorespiration, and sustained chlorophyll levels (<xref ref-type="bibr" rid="B45">Yamori et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B50">Zhou et&#xa0;al., 2022</xref>). At low temperature, an increased CO<sub>2</sub>/O<sub>2</sub> solubility ratio favors Rubisco carboxylation over oxygenation, which is generally associated with reduced photorespiration and helps sustain carbon assimilation efficiency under cold conditions (<xref ref-type="bibr" rid="B33">Sage and Kubien, 2007</xref>). From DAT 2 to 7, <italic>A</italic> slightly declined at both 18 and 25&#xa0;&#xb0;C (<xref ref-type="table" rid="T2"><bold>Table&#xa0;2</bold></xref>) despite stable ETR (<xref ref-type="fig" rid="f4"><bold>Figures&#xa0;4C, D</bold></xref>), indicating possible feedback inhibition due to sink limitation or TPU bottlenecks (<xref ref-type="bibr" rid="B1">Adler et&#xa0;al., 2025</xref>). This imbalance between electron transport and carbon fixation likely contributed to the gradual decline in the ETR/<italic>A</italic> slope (<xref ref-type="fig" rid="f7"><bold>Figure&#xa0;7</bold></xref>).</p>
<p>In contrast, high temperature induced transient inhibition of carbon assimilation followed by strong recovery. At 32&#xa0;&#xb0;C, <italic>A</italic> was initially suppressed significantly (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6A</bold></xref>) despite only slight reductions in &#x3a6;<sub>PSII</sub> (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4A</bold></xref>), indicating a temporary decoupling between photochemistry and carbon assimilation. Although <italic>g</italic><sub>s</sub>, <italic>E</italic>, and <italic>C</italic><sub>i</sub> were elevated at 32&#xa0;&#xb0;C on DAT 2, <italic>A</italic> remained suppressed, indicating that carbon assimilation was initially limited by non-stomatal factors such as enhanced photorespiration or reduced Rubisco activity rather than CO<sub>2</sub> diffusion (<xref ref-type="bibr" rid="B37">Sharkey and Zhang, 2010</xref>; <xref ref-type="bibr" rid="B45">Yamori et&#xa0;al., 2014</xref>). As acclimation progressed, <italic>A</italic> increased substantially by DAT 7 particularly under the high temperature and high light combination (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6B</bold></xref>), coinciding with pronounced increases in <italic>g</italic><sub>s</sub> and E (<xref ref-type="fig" rid="f6"><bold>Figures&#xa0;6F, G</bold></xref>), which in turn increased the slope of the <italic>A</italic> vs. ETR relationship (<xref ref-type="fig" rid="f7"><bold>Figure&#xa0;7</bold></xref>). Compared to <italic>g</italic><sub>s</sub> and <italic>E</italic>, <italic>C</italic><sub>i</sub> remained slightly higher under the high temperature but was lower under high light intensity, suggesting that increased CO<sub>2</sub> diffusion through stomatal opening was largely balanced by enhanced carbon assimilation rates. This adaptation was also supported by higher <italic>V</italic><sub>c,max</sub> and TPU at elevated temperatures with high light combination at DAT 7 (<xref ref-type="fig" rid="f8"><bold>Figure&#xa0;8</bold></xref>), indicating metabolic acclimation of carbon assimilation (<xref ref-type="bibr" rid="B8">Farquhar et&#xa0;al., 1980</xref>; <xref ref-type="bibr" rid="B40">Urban et&#xa0;al., 2017</xref>). Together, these stomatal and biochemical adjustments led to a disproportionate increase in carbon assimilation relative to photochemical efficiency, resulting in a divergence between <italic>A</italic> and &#x3a6;<sub>PSII</sub> observed under high temperature conditions.</p>
<p>Biomass and shoot water content revealed a decoupling from photosynthetic rate. Although &#x3a6;<sub>PSII</sub> at 18&#xa0;&#xb0;C recovered to levels comparable to 25&#xa0;&#xb0;C, and <italic>A</italic> at 32&#xa0;&#xb0;C exceeded that at 25&#xa0;&#xb0;C by DAT 7, shoot biomass remained highest at 25&#xa0;&#xb0;C (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4</bold></xref>). This indicates that improved photochemical efficiency or CO<sub>2</sub> assimilation did not necessarily translate into biomass accumulation. This may reflect limitations imposed by downstream processes such as respiratory carbon losses or carbon allocation dynamics (<xref ref-type="bibr" rid="B35">Seydel et&#xa0;al., 2022</xref>), although these mechanisms were not directly assessed in this study. Shoot water content was also reduced under thermal extremes (<xref ref-type="table" rid="T4"><bold>Table&#xa0;4</bold></xref>), likely due to transpirational loss under heat and impaired water uptake or cell expansion under cold (<xref ref-type="bibr" rid="B48">Yu et&#xa0;al., 2025</xref>). High light further decreased water content and increased chlorophyll concentration, consistent with physiological and structural acclimation observed in this study (<xref ref-type="bibr" rid="B49">Zha et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B50">Zhou et&#xa0;al., 2022</xref>).</p>
<p>Taken together, these results indicate that instantaneous CF parameters and gas exchange responses do not necessarily reflect final growth outcomes. However, cumulative ETR, integrated over the experimental period, emerged as a useful predictor of biomass accumulation independent of temperature (<xref ref-type="fig" rid="f9"><bold>Figure&#xa0;9</bold></xref>). This result indicates that integrating photochemical performance across time retains useful information relevant to biomass accumulation. Previous studies have suggested that the predictive value of CF parameters for crop yield improves when temporal dynamics are incorporated (<xref ref-type="bibr" rid="B27">Moriyuki and Fukuda, 2016</xref>). In particular, Moriyuki and Fukuda highlighted the importance of developing a high-resolution, time-course CF measurement system to evaluate the potential of CF-based indices for growth prediction, rather than relying on single time-point observations.</p>
<p>Importantly, the cumulative ETR&#x2013;biomass relationship identified here was derived from short-term (7-day) experiments under controlled conditions. While these results demonstrate the potential of temporally integrated CF metrics to link photochemical performance with biomass accumulation, further validation over longer growth periods and across different crop species and cultivars is required to assess the broader applicability of this approach.</p>
</sec>
<sec id="s4_4">
<label>4.4</label>
<title>High-temporal resolution CF monitoring system for real-time growing condition control</title>
<p>CF offers a comprehensive and reliable method for assessing photochemical efficiency and plant stress responses. Unlike gas exchange measurements, CF provides detailed information on the function of PSII and electron transport, including parameters such as &#x3a6;<sub>PSII</sub>, &#x3a6;<sub>NPQ</sub>, &#x3a6;<sub>NO</sub>, qL, and <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032;, which help characterize how different stress conditions affect photosynthetic capacity (<xref ref-type="bibr" rid="B18">Kalaji et&#xa0;al., 2016</xref>). These indicators reveal whether stress is transient or sustained, photoinhibitory or protective, which gas exchange measurements alone cannot distinguish. A decline in <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> is a widely accepted marker of photoinhibition under temperature and light stress (<xref ref-type="bibr" rid="B25">Maxwell and Johnson, 2000</xref>). In this study, <italic>A</italic> recovered over time under the high temperature and high light combination due to increased <italic>g</italic><sub>s</sub>, but <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> remained low, indicating sustained photoinhibitory damage that would have been overlooked using CO<sub>2</sub> exchange alone (<xref ref-type="bibr" rid="B43">Willits and Peet, 2001</xref>).</p>
<p>Conventional methods for determining <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> require a long period of dark adaptation, which would interrupt ongoing light treatments if measurements are conducted during the photoperiod (<xref ref-type="bibr" rid="B43">Willits and Peet, 2001</xref>), while measurements on detached leaves may not reflect real-time physiological responses (<xref ref-type="bibr" rid="B47">Yu and Chen, 2023</xref>). Instead, parameters such as <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032; and qL can provide insights into PSII photochemical efficiency and electron transport limitations (<xref ref-type="bibr" rid="B3">Baker et&#xa0;al., 2007</xref>), but they require accurate measurement of <italic>F</italic><sub>o</sub>&#x2032;, which can only be obtained when all PSII reaction centers are open and is therefore challenging under ambient light conditions (<xref ref-type="bibr" rid="B19">Kramer et&#xa0;al., 2004</xref>). In this study, far-red LED lighting was integrated into the CF monitoring system in the growth chamber (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>), enabling rapid and automated estimation of <italic>F</italic><sub>o</sub>&#x2032; and consequently <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032; and qL without long dark adaptation or interruption of daytime conditions (<xref ref-type="bibr" rid="B25">Maxwell and Johnson, 2000</xref>; <xref ref-type="bibr" rid="B39">Tietz et&#xa0;al., 2017</xref>).</p>
<p>Real-time, high-frequency CF monitoring enabled early detection of plant stress and subtle changes over time in photosynthetic performance. Unlike conventional gas exchange measurements, which are typically conducted at daily or less frequent intervals, CF can be collected non-destructively at much higher temporal resolution (<xref ref-type="bibr" rid="B25">Maxwell and Johnson, 2000</xref>; <xref ref-type="bibr" rid="B28">Moustaka and Moustakas, 2023</xref>). In this study, CF parameters were measured every 30 minutes, enabling the visualization of diurnal patterns and stress dynamics in real-time. This level of detail is critical for detecting rapid photochemical responses and interpreting acclimation processes. The system&#x2019;s flexibility, enabled by serial communication between the chlorophyll fluorometer and the datalogger, allows customized measurement regimes based on experimental objectives (<xref ref-type="bibr" rid="B30">Nam et&#xa0;al., 2025</xref>; <xref ref-type="bibr" rid="B42">van Iersel et&#xa0;al., 2016</xref>).</p>
<p>Real-time CF data can support adaptive control of growing conditions in CEA systems. CF monitoring systems have the potential to optimize energy use, maximize productivity, and protect plants from environmental stress by responding to photochemical indicators such as &#x3a6;<sub>PSII</sub> and <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032; (<xref ref-type="bibr" rid="B2">Ahlman et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B4">Baker and Rosenqvist, 2004</xref>). In previous studies, CF-based biofeedback systems were used to adjust LED lighting intensity to maintain target ETR or &#x3a6;<sub>PSII</sub> as plant responses changed, reducing energy use while sustaining photosynthetic performance (<xref ref-type="bibr" rid="B30">Nam et&#xa0;al., 2025</xref>; <xref ref-type="bibr" rid="B42">van Iersel et&#xa0;al., 2016</xref>). For example, based on our results, high light combined with low temperature induced photoinhibition, which could be mitigated by temporarily dimming LED lights. As plants acclimate and recover their photosynthetic efficiency, light intensity can be gradually restored or even increased to promote growth. In vertical farms, continuous lighting with a 24-h photoperiod and spectra with a high blue fraction or ultraviolet (UV) LED lighting are being actively investigated for their effects on crop productivity and quality. Under these conditions, real-time CF monitoring combined with biofeedback light control can be used to diagnose light stress and track acclimation processes, allowing dynamic adjustment of light intensity and spectrum based on photochemical responses. Such plant-driven lighting strategies may help prevent severe photoinhibition while maintaining photosynthetic performance. This approach can also be extended to a comprehensive CEA environmental control system using CF parameters to regulate not only lighting but also temperature, ventilation, and irrigation, applicable in both vertical farming systems and greenhouses (<xref ref-type="bibr" rid="B30">Nam et&#xa0;al., 2025</xref>; <xref ref-type="bibr" rid="B42">van Iersel et&#xa0;al., 2016</xref>).</p>
</sec>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusion</title>
<p>This study applied high-temporal resolution CF monitoring to evaluate photosynthetic responses to varying light and temperature conditions. High light and low temperature stress initially reduced PSII efficiency, but gradual acclimation over one week was observed, indicated by decreases in &#x3a6;<sub>NO</sub> and increases in <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub>, rather than by changes in NPQ. In contrast, high temperature with high light increased CO<sub>2</sub> assimilation markedly over time due to enhanced stomatal conductance, yet <italic>F</italic><sub>v</sub>/<italic>F</italic><sub>m</sub> remained suppressed, suggesting sustained photoinhibition. The high-frequency CF monitoring system, operating every 30 minutes, enabled the real-time detection of subtle changes and diurnal trends in photochemical responses, capturing stress responses and acclimation patterns that would not have been evident from daily measurements or gas exchange data alone. The integration of light-adapted parameters requiring far-red illumination, such as qL and <italic>F</italic><sub>v</sub>&#x2032;/<italic>F</italic><sub>m</sub>&#x2032;, allowed for a more comprehensive interpretation of photochemical limitations and electron transport efficiency. Although CF parameters did not always align with downstream carbon assimilation or biomass accumulation, they provided valuable insights into photochemical bottlenecks and stress status. These findings highlight the potential of CF monitoring to support real-time environmental decision-making in CEA systems, for example, by identifying photochemical stress thresholds that could inform adaptive adjustments in supplemental light intensity or thermal management.</p>
</sec>
</body>
<back>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p></sec>
<sec id="s7" sec-type="author-contributions">
<title>Author contributions</title>
<p>SN: Visualization, Investigation, Validation, Conceptualization, Formal analysis, Writing &#x2013; original draft, Data curation, Methodology. RF: Funding acquisition, Project administration, Resources, Writing &#x2013; review &amp; editing, Validation, Supervision, Visualization.</p></sec>
<ack>
<title>Acknowledgments</title>
<p>We are deeply indebted to the late Professor Dr. Marc W. van Iersel, who provided the initial conceptualization and experimental-design framework for this study. We thank the Horticultural Physiology and the CEA Crop Physiology and Production Laboratories for the technical support and Dr. Cari Peters and JR Peters for fertilizer donation.</p>
</ack>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
<p>The author RF declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.</p></sec>
<sec id="s10" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was used in the creation of this manuscript. ChatGPT (GPT-4, June 2025 version; OpenAI, San Francisco, CA, USA) was used to help edit the language and readability of the manuscript, and DALL&#xb7;E 3 (OpenAI, accessed via ChatGPT in June 2025) was used to draft schematic elements of <xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>. All AI-assisted content was thoroughly reviewed, edited, and verified by the authors, who take full responsibility for the published material.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p></sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec>
<sec id="s12" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fpls.2026.1733839/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fpls.2026.1733839/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Supplementaryfile1.docx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/></sec>
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<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3293613">Yanwei Liu</ext-link>, Kunming University of Science and Technology, China</p></fn>
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